Design and Modelling of Energy Sufficiency Measures in Mobility in Energy Communities


Master project
Fall 2024

IPESE would like to complete its team with a master’s student capable of collaborating proactively with the project partners, contributing their own ideas and implementing them rigorously in energy system models. The main objective of this master’s project is to bridge the gap between the building sector, energy infrastructure and mobility. Spatial and temporal boundaries between living and working have become blurred by social processes of flexibilization and digitalization. These aspects have to be considered in the energy transition to synergize cross-sectorial demands and consider social paradigm shifts. The project is closely integrated with the SFOE’s Swice project, which aims to complement the techno-economic approach to energy transition with human well-being considerations. As a result, real-life case studies and energy sufficiency interventions are being carried out in the Living Lab of Suurstoffi (Luzern). These interventions form the basis of the scenario modelled in REHO. As part of this master’s project, the student will carry out the following tasks:

  • Assess the impact of energy sufficiency measures (shared mobility, home office, mixed neighborhoods) in energy communities using the open-source REHO model.

  • Run a sensitivity analysis on mobility profiles based on population segments

  • Quantify the needs for public transportation in the city of Luzern and assess the potential of local bus charging in energy communities. Identify places for transportation network reinforcement

  • Link the local needs of mobility with national transportation network using EnergyScope

The student will have the opportunity to take part in workshops to help design social interventions in the field. Based on this experience, she/he will draw on the analysis of social science researchers to model their inputs to energy models. Pro-activity and curiosity are just as necessary as a good knowledge of Python.

The project will be supervised by Cédric Terrier (PhD student IPESE) and Dr. Eduardo Pina (Postdoc IPESE). If interested, please send your CV, with a short motivation letter, to cedric.terrier@epfl.ch.